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In this paper, we propose an adaptive locality weighted multisource joint sparse representation classification (ALWMJ-SRC) model for the classification of multisource remote sensing data. Although the notion of multitask joint sparsity has been recently developed for data fusion and has shown to be effective for various applications, in this paper, we suggest that there are important limitations stemming...
Exploiting disparate features from potentially different data sources with multiple-kernel based machine learning is a promising approach for analyzing geo-spatial data. A mixture-of-kernel approach can facilitate construction of a more effective training data pool with Active Learning (AL). In addition, this could alleviate the computational burden in AL implementations. Kernel based learning requires...
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